Distinguishing Vaccinium species by chemical fingerprinting based on NMR spectra, validated with spectra collected in different laboratories.

A method was developed to distinguish Vaccinium species based on leaf extracts using nuclear magnetic resonance spectroscopy. Reference spectra were measured on leaf extracts from several species, including lowbush blueberry (Vaccinium angustifolium), oval leaf huckleberry (Vaccinium ovalifolium), and cranberry (Vaccinium macrocarpon). Using principal component analysis, these leaf extracts were resolved in the scores plot. Analysis of variance statistical tests demonstrated that the three groups differ significantly on PC2, establishing that the three species can be distinguished by nuclear magnetic resonance. Soft independent modeling of class analogies models for each species also showed discrimination between species. To demonstrate the robustness of nuclear magnetic resonance spectroscopy for botanical identification, spectra of a sample of lowbush blueberry leaf extract were measured at five different sites, with different field strengths (600 versus 700 MHz), different probe types (cryogenic versus room temperature probes), different sample diameters (1.7 mm versus 5 mm), and different consoles (Avance I versus Avance III). Each laboratory independently demonstrated the linearity of their NMR measurements by acquiring a standard curve for chlorogenic acid (R(2) = 0.9782 to 0.9998). Spectra acquired on different spectrometers at different sites classifed into the expected group for the Vaccinium spp., confirming the utility of the method to distinguish Vaccinium species and demonstrating nuclear magnetic resonance fingerprinting for material validation of a natural health product.

Quantification of chlorogenic acid and hyperoside directly from crude blueberry (Vaccinium angustifolium) leaf extract by NMR spectroscopy analysis: single-laboratory validation.

A single-laboratory-validated NMR spectroscopy method was established for determining the quantity of chlorogenic acid and hyperoside from crude extract material of blueberry leaves of the species Vaccinium angustifolium var. laevifolium House. The calibration curve of chlorogenic acid showed a highly linear regression, R = 0.99998. NMR spectroscopy identification and quantification of the constituents directly from the mixture, within the error of HPLC-diode array detector analysis, were determined as 7.53 mM chlorogenic acid (64.0 mg chlorogenic acid/g powdered leaf) and 0.77 mM hyperoside (8.58 mg hyperoside/g powdered leaf). The LOD was calculated to be 0.01 mM and the LOQ 0.01 mM by the 9 min and 13 s NMR spectroscopy experiment utilized. The assay showed no significant interference from different field strengths, extraction mesh size, gravimetric scale precision, NMR spectroscopy tube type, pulse program, amount of starting dry material, or day-to-day operation. The robustness of NMR spectroscopy as a means of definitively monitoring chlorogenic acid and hyperoside content directly from crude extracts was demonstrated by Youden statistical analysis.

Synovial fluid metabolomics in different forms of arthritis assessed by nuclear magnetic resonance spectroscopy.

OBJECTIVES: Currently there are no reliable biomarkers in the synovial fluid available to differentiate between septic and non-septic arthritis or to predict the prognosis of osteoarthritis, respectively. Nuclear magnetic resonance (NMR) spectroscopy is an analytical technique that allows a rapid, high throughput metabolic profiling of biological fluids or tissues. METHODS: Proton (1H)-nuclear magnetic resonance (NMR) spectroscopy was performed in synovial fluid samples from patients with septic arthritis, crystal arthropathy, different forms of inflammatory arthritis or osteoarthritis (OA). The metabolic environment based on the low molecular weight components was compared in disease subsets and principal component analysis (PCA) was performed. RESULTS: Fifty-nine samples from patients with OA, gout, calcium pyrophosphate disease, spondylarthritis, septic arthritis and rheumatoid arthritis (RA) were analysed. NMR yielded stable and reproducible metabolites over time. Thirty-five different metabolites as well as paracetamol and ibuprofen were identified in synovial fluid. The metabolic profile of septic arthritis assessed by PCA was distinguishable from the other samples whereas no differences were seen in OA compared to crystal-associated arthritis, RA or spondylarthritis. CONCLUSIONS: 1H-NMR is a fast analytic tool with possible implications in synovial fluid diagnostics. A distinctive metabolism is observed in septic arthritis whereas metabolites in OA are similar to those in inflammatory arthritis.